Matrix rank refers to the dimension of the vector space generated by its rows or columns, indicating the number of linearly independent rows or columns. It is crucial for understanding the solutions of linear systems, as a higher rank suggests more unique solutions while a lower rank indicates potential degeneracy. The rank can reveal properties such as whether a matrix is invertible or the nature of its null space. Examples illustrate how to calculate rank and its implications for system solutions. Overall, matrix rank is a fundamental concept in linear algebra with significant applications in various mathematical and engineering fields.