Answer:
Training a model using labeled data and using this model to predict the labels for new data is known as: Supervised Learning.
Step-by-step explanation:
Supervised learning is a set of techniques that allows future predictions based on behaviors or characteristics analyzed in labeled historical data. A label is nothing more than the output that the data set has returned for historical data, already known. In supervised learning, it assumes that we start from a previously labeled data set, that is, we know the value of the target attribute for the data set that we have.