This area is known as supervised learning. In supervised learning, a machine learning algorithm is trained on a labeled dataset, where the input data is paired with the correct output or target variable. The algorithm learns to map input data to the correct output by generalizing patterns or rules from the examples it was trained on. This allows the algorithm to make predictions on new, unseen data based on the patterns it has learned during training.
