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Understanding binary tree traversal is fundamental when learning about data structures and algorithms. A binary tree is a hierarchical data structure in which each node can have at most two children, often referred to as the left and right children.

Traversal algorithms determine the order in which nodes of a binary tree are visited. There are several types of traversals, with postorder traversal being one of the primary methods. In postorder traversal, each node is visited after its subtrees. Therefore, the order of operations begins with traversing the left subtree, followed by the right subtree, and concluding with the processing of the current node.

• Left Subtree: Traverse and process all nodes in the left subtree.
• Right Subtree: Traverse and process all nodes in the right subtree.
• Current Node: Visit and, if applicable, perform an action at the current node, such as printing its value.

Postorder traversal is often used when recursively deleting a tree, because it ensures that child nodes are dealt with before their parents.

Pseudocode is a simple way of writing algorithms in plain English, adopting the structure of coding without adhering to the syntax of a specific programming language. It's a bridge between human language and computer code, aimed at showcasing the logic of an algorithm in a readable manner.

The pseudocode for the postorder traversal function allows you to visualize the process without getting bogged down by the intricacies of a programming language's syntax. Let's demystify the main parts:

• Function Definition: The algorithm begins by defining a function that accepts a node as its parameter.
• Base Case: A key part of recursion in pseudocode is establishing a base case to prevent infinite loops. This is typically a condition that, when met, will stop the recursive calls. In our case, if a node is null, the function will return without making further calls.
• Recursive Calls: The function makes recursive calls first to visit the left subtree and then the right subtree.
• Data Processing: After the subtrees are traversed, the data at the current node is processed (e.g., printed).

Recursion is a powerful concept in programming where a function calls itself in order to solve smaller instances of a larger problem. This technique can simplify complex problems, especially those that are naturally hierarchical or that can be broken down into similar sub-problems.

However, recursive functions have to be designed carefully to prevent infinite loops and stack overflows. They must have a base case that eventually terminates the recursion. In the context of a postorder traversal, the base case occurs when a node is null, signaling that the recursive function should not make any further calls and begin to unwind.

The recursive calls in the postorder traversal function effectively manage the depth-first search to process all nodes. Each invocation of the function is a step deeper into the tree, and when a leaf node is reached, the function simplifies until the entire tree has been traversed.

It's important to understand the 'call stack' during recursion, which keeps track of the different states of the function as it traverses the tree. Through each recursive call, the current node is pushed to the stack, and once its subtree calls are complete, it is popped out, ensuring nodes are visited in the correct postorder sequence.