Traditional machine learning algorithms rely on a set of pre-defined features to make predictions. In contrast, deep learning algorithms learn these features from the data itself, using a hierarchical structure of artificial neural networks. This allows deep learning models to automatically extract complex features and patterns from raw data, making them well-suited for tasks like image recognition and natural language processing.