In many cases, machine learning is very complicated. This is not that case.
A type of machine learning model that assigns a label to an input based on a series of questions organized in a tree structure.
This may sound complicated, but it's basically just a flowchart that is used to make a decision. Like this one:
Decision trees can become quite complex, with many layers and many questions. There are algorithms to find the best set of questions to ask and in what order. But regardless of how complicated a decision tree is, these models are generally regarded as interpretable because given a decision, it is possible to trace back up the tree to find out why the model made that decision.
If you decided on the Cabernet Sauvignon, we know it's because you like tannic red wines.