Classification and Regression Trees (CART) are decision tree frameworks used for predictive modeling, where the tree is built through a process of splitting data points using feature values to create branches. This recursive partitioning continues until a stopping criterion is met, effectively simplifying complex datasets into interpretable models for classification or regression tasks.