The type of machine learning that involves training algorithms on labeled data is known as supervised learning. In this approach, the model learns from a dataset that contains input-output pairs, where the correct output (or label) is provided for each input example. The algorithm identifies patterns and relationships within the data to predict outcomes for new, unseen data. Supervised learning is commonly used in applications such as image recognition, spam detection, and financial forecasting, making it a fundamental technique in machine learning.