Decision Trees Nodes vs Leaves Definition
Leaf nodes are the nodes of the tree that have no additional nodes coming off them. They don't split the data any further; they simply give a classification for examples that end up in that node. In your example tree diagram, the nodes that say 'Large', 'Medium' or 'Small' are leaf nodes. The other nodes in the tree are interchangeably called split nodes, decision nodes or internal nodes.

In gradient boosting algorithms, a number of decision trees are grown. Each tree is grown until some stopping criteria is met. One kind of stopping criteria is the maximum number of leaves in the tree. At each stage of growing a decision tree, a leaf node is turned into a split node by creating a yes/no question (we call this a binary split), and two new leaf nodes are created which correspond to each side of the split. Once the total number of leaf nodes in the tree reaches the limiting value, the tree building algorithm stops and begins building the next tree.