Signal to noise ratio is a measure that compares the strength of the desired signal, or useful information, to the background noise, or irrelevant information.
To illustrate these concepts consider two scenarios.
Imagine your hiking in a forest on a foggy day, miles from the nearest road. You and your hiking partner stop for a break and while resting you have a quiet conversation. You have no trouble hearing each other even though you’re both talking in library-voices.
Now imagine you’re at a rip-roaring New Years Eve party; the music is loud and everyone is whooping it up, having a good time. You’re shouting into the ear of the person beside you trying to have a conversation but you’re only catching half of what they’re saying.
In the forest you have a dramatic difference between the signal (your voice) and the background noise (the deadened sounds of the forest in fog). It is easy to pick out the sounds that make up words and you can easily carry on your conversation in hushed tones.
The party is a radically different situation. The background noise is so loud that even shouting, it’s hard to pick out the signal from the noise.
Electricity is noisy. The electricity that powers the digital sensor in your camera causes noise. When that noise is significant as compared to the signal (the scene we’re shooting) it can cause problems. An easy way to visualize the noise in your camera is to take a picture with the lens cap on. The resultant image should be a uniform field of black, but it’s not. When zoomed in you should see speckles of color and light that were triggered by the background noise in the sensor. Here’s an example shot with my Canon 5DMII.