Supervised Learning

The most common machine learning paradigm, where a model is trained on a labeled dataset, each input paired with the correct output, and learns to map inputs to outputs by minimizing the difference between its predictions and the true labels. Classification and regression are the two primary variants, and most practical ML systems in production today were built with supervised learning at their core.
See also: self-supervised learning, semi-supervised learning.