Linear regression entails matrix inversion, and this is the mechanism via which collinearity affects linear regression in case that the matrix is singular.
However in logistic regression, the estimation of coefficients is based on some likelihood function instead of normal equation as is used in linear regression.
Since there is no closed form expression for obtaining the solution, iterative calculation is instead used for the estimation. There is no way collinearity kicks in the process.