Can k-fold CV help reduce sampling bias?

I am currently writing a thesis and have surveyed about 500 people and I am using it as input in a supervised model. Due to some time limitations there was some bias in the sampling process itself.

I have used cross validation before in a statistical learning intro course (but it was barely covered) and know about the bias-variance trade off, but it is still not entirely clear to me.

Can I use k-fold cross-validation to reduce sampling bias from the survey (or at least compute some confidence intervals for the model coefficients), or is it only model bias that can be reduced?