Supervised learning is the branch of machine learning where a model learns from labeled examples — input-output pairs where the correct answer is provided — to make predictions on new, unseen data. The two main tasks are classification (predicting categories, like spam vs. not spam) and regression (predicting continuous values, like house prices). It is the most widely used ML paradigm: most business applications — credit scoring, demand forecasting, medical diagnosis — rely on supervised learning.