Probability distribution
Also: distribution, probability mass function, probability density function, PMF, PDF
For a discrete variable it is a probability mass function P(X = x); for a continuous one a density f(x), where probability is the area under the curve. A model's predictions are usually a distribution over outputs.
Σₓ P(X = x) = 1 or ∫ f(x) dx = 1
Example
A fair die has P(X = k) = 1/6 for k = 1…6. A classifier that outputs (cat 0.7, dog 0.2, bird 0.1) is also a distribution: three non-negative numbers summing to 1.