standard error of the mean is the population standard deviation divided by the square root of the sample size - you are given both of these
--> the standard error of the mean is the standard deviation of sample means (i.e., approximately what it would be if you drew many samples, computed the mean of each sample, then computed the standard deviation of those means)
(B and C)
You need to compute a z-score (for 19.5 in B, and for both 25.5 and 27 in C) which is the sample mean minus the population mean, then this difference divided by the standard error of the mean. Don't use absolute values - it's OK to get a negative z-score. A z-score indicates how many standard deviations away from the center of the normal curve. If it's negative, it's to the left of center, if it's positive, it's to the right.....
For B, you need to find the proportion (% of the total area) of the curve above the z-score for 19.5
For C, you need to find the proportion (% of the total area) of the curve in-between the z-scores for 25.5 and 27
I'm sure there are examples in your textbook that are exactly lke this.....