Multi-Label Classification predicts multiple labels for a single sample, rather than just one. Tasks like tagging an image with multiple objects or assigning multiple genres to a song fall under this category. Evaluation metrics include hamming loss, subset accuracy, and the macro/micro average of precision/recall.