Sampling errors are linked to the fact that we seek out part of the population. If we repeated the sampling and we chose a different sample, we would probably have different results. Generally, we calculate the confidence level for a statistical measure to give us an idea of how precise it is. Sampling error depends on the size of the sample and the statistics we measure.
We talk about population bias when we have underrepresentation or we have difficulty covering part of the population. That means the results may not be representative if a segment of the population is not covered and if that segment had characteristics that were different from what we were seeking to measure. That type of situation could lead to bias.