The mean squared error is the average squared error between the actual value and the predicted value and can be interpreted as the squared +/- difference that would expected to see on average from a predicted value and the actual value.

If dealing with a metric like dollars, MSE would be the average +/- difference in the units squared or in other words it is saying that the model is off by +/- 1,562,500 $^{2}. Note that it is in dollars squared.