What would be the consequences for the OLS estimator heteroscedasticity is present in a regression model but ignored?

It will be ignored

It will be inconsistent

It will be inefficient

All of A, B and C will be true

If heteroscedasticity is present in a regression model but ignored, the Ordinary Least Squares (OLS) estimator will still be unbiased, but it will not be efficient.
This means that the estimator will not have the smallest possible variance, and the estimates may not be precise.