The Central Limit Theorem states:

The smaller the standard error of the mean, the closer it is to the population mean.

The mean of a sampling distribution of means is equal to the population mean.

The smaller the sample size, the closer the sample mean approximates the population mean.

A sample with a larger standard of error of the mean still has a mean that approximates the population mean.