Answer:
The distribution is skewed (either to the left or to the right).
Step-by-step explanation:
Skewness is the measure of how symmetric the distribution of the data is around its mean. It can be skewed either to the left or to the right (meaning that one of the "tails" of the distribution is longer than the other). This means that the mass your data set's observations tends to accumulate more around one extreme of the distribution than around the other.
A strictly symmetric, normal distribution would have a skewness measure of 0.
