A label is the target value or category associated with an example in supervised learning. During training, the model learns relationships between input features and labels so it can predict labels for new examples.
The element to be predicted with the machine learning model. For example, the breed of dog or a future stock price.
In supervised machine learning, the "answer" or "result" portion of an example. Each labeled example consists of one or more features and a label. For example, in a spam detection dataset, the label would probably be either "spam" or "not spam." In a rainfall dataset, the label might be the amount of rain that fell during a certain period. See Supervised Learning in Introduction to Machine Learning for more information.
In machine learning, data for which you already know the target or "correct" answer.