The machine learning process used for predicting outcomes based on historical data is known as supervised learning. This approach involves training a model on labeled datasets, where input-output pairs exist. By learning the relationship between inputs and outcomes, the model can make predictions on new, unseen data. Supervised learning is commonly used in applications like classification and regression, where accurate predictions are necessary for decision-making processes.