What term describes the type of machine learning where the model is trained on labeled data?

Supervised learning is the term that refers to the type of machine learning where a model is trained on labeled data. In this approach, the dataset used for training includes inputs paired with their corresponding outputs, allowing the model to learn the relationship between them. The labeled data serves as a guide, enabling the algorithm to make predictions or decisions based on new, unseen data.

During the training process, the model uses the provided labels to adjust its parameters, minimizing the difference between its predictions and the actual outcomes. This learning method is particularly effective for tasks such as classification and regression, where the objective is to map input data to specific labels. Supervised learning is foundational in many machine learning applications, where clarity and accuracy in predictions are essential.