A convex cone is a subset of a vector space that is closed under linear combinations with positive coefficients, meaning if you take any two points in the cone and any two non-negative scalars, the resulting combination is still within the cone. Convex cones are fundamental in optimization and are used to describe feasible regions in linear programming and other mathematical models.