How does feature selection happen inside Decision Trees?

Decision Trees perform implicit feature selection by choosing features that maximize impurity reduction at each split.

At each node, the algorithm evaluates all features and selects the one that provides the best split according to impurity metrics. Features not used in any split are effectively ignored. This makes decision trees naturally perform embedded feature selection, unlike filter or wrapper methods.