There is also the interesting interpretation of logistic regression as a latent choice/utility model, where unobserved variation in utility is modeled using the logistic distribution. In this interpretation, the sigmoid function arises as the CDF of the logistic distribution.

This interpretation is also nice as it shows the natural relationship between logistic and probit regression. Probit regression arises when the unobserved utility is modeled with a Gaussian distribution.