To the best of my understanding, the Monte Carlo tree search (MCTS) algorithm is an alternative to minimax for searching a tree of nodes. It works by choosing a move (generally, the one with the highest chance of being the best), and then performing a random playout on the move to see what the result is. This process continues for the amount of time allotted.
This doesn't sound like machine learning, but rather a way to traverse a tree. However, I've heard that AlphaZero uses MCTS, so I'm confused. If AlphaZero uses MCTS, then why does AlphaZero learn? Or did AlphaZero do some kind of machine learning before it played any matches, and then use the intuition it gained from machine learning to know which moves to spend more time playing out with MCTS?