Rank is a fundamental concept in linear algebra that indicates the dimension of the vector space generated by the columns or rows of a matrix, reflecting its non-degeneracy and the maximum number of linearly independent column or row vectors. It is crucial in determining the solvability of linear systems, the invertibility of matrices, and in various applications such as data compression and machine learning.