Mostly, it has great support for service discovery for many major cloud and container platforms (Kubernetes, Marathon, EC2, Azure, Zookeeper, Consul, ...). So it can not only go out and pull metrics data directly from instances as they float around your dynamic cluster scheduler, but also attach identity metadata (as provided by the service discovery) to the time series collected from each instance. For example, you may map EC2 tags or Kubernetes labels into your Prometheus time series labels to give you more useful metrics. There's also a way to plug in your own custom service discovery. Also, Kubernetes exports native Prometheus metrics since quite a while already.

Borg inspired Kubernetes. Borgmon inspired Prometheus. So naturally it works well together with a dynamically scheduled world.