The question asks about the type of machine learning algorithm used when the dataset includes labeled data with known outcomes. Supervised Learning is characterized by the use of labeled datasets, where each data point has a corresponding output or "label." The algorithm learns a mapping from inputs to outputs based on these known outcomes. Transfer Learning involves reusing a pre-trained model on a new, related task. While it often uses labeled data for fine-tuning, its core definition is about knowledge transfer, not solely the presence of labeled data. Unsupervised Learning deals with unlabeled data, aiming to find patterns or structures within the data without prior knowledge of outcomes. Reinforcement Learning involves an agent learning through trial and error by interacting with an environment and receiving rewards or penalties. It does not primarily rely on a pre-existing dataset of labeled outcomes. Therefore, the type of machine learning algorithm used with labeled data and known outcomes is Supervised Learning. The correct option is Supervised Learning.