https://www.wikiwand.com/en/Instance-based_learning
In machine learning, instance-based learning (sometimes called memory-based learning) is a family of learning algorithms that, instead of performing explicit generalization, compares new problem instances with instances seen in training, which have been stored in memory.
A common example is Nearest-neighbour classification