In computational learning theory in mathematics, a concept over a domain X is a total Boolean function over X. A concept class is a class of concepts. Concept classes are a subject of computational learning theory.

Concept class terminology frequently appears in model theory associated with probably approximately correct (PAC) learning. In this setting, if one takes a set Y as a set of (classifier output) labels, and X is a set of examples, the map ${\displaystyle c:X\to Y}$, i.e. from examples to classifier labels (where ${\displaystyle Y=\{0,1\}}$ and where c is a subset of X), c is then said to be a concept. A concept class ${\displaystyle C}$ is then a collection of such concepts.

Given a class of concepts C, a subclass D is reachable if there exists a sample s such that D contains exactly those concepts in C that are extensions to s. Not every subclass is reachable.