F1 score is a combination of recall and precision. It also a shorthand to measure how accurate and useful the result is.
Accuracy is a simple fraction of correctly classified objects over total number of objects.
It can be misleading to only focus on accuracy, especially when data labels are imbalanced, even if data is representative. Certain scenarios are simply more prevalent in the population data. For example, by definition orphan diseases are the minority data points in the real world.