A ReLU, or Rectified Linear Unit is a function where the minimum value is zero. The result of the composition of multiple linear functions is also a linear function. Thus, a neural network that only uses compositions of linear functions can only solve problems that linear functions can.
By introducing non-linearity in-between linear functions (by adding ReLUs, for example), non-linear functions are able to be created out of the composition.