Added implementation of KNN algorithm

Added implementation of KNN algorithm from Scratch.

Python/ML Algorithms/kNearestNeighbour.py

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+import matplotlib.pyplot as plt
+import numpy as np
+import math 
+f=[[10,5],[40,7],[3,2],[5,3]]
+l=['good','good','bad','bad']
+x=[]
+y=[]
+s=len(set(l)) #shows all categories present
+for i in range(len(f)):
+    f1=f[i][0]
+    x=np.append(x,f1)
+    f2=f[i][1]
+    y=np.append(y,f2)
+print(x," ",y)
+for i in range(len(f)):
+    if (l[i]== 'good'):
+        plt.plot(x[i],y[i],'r*')
+    else:
+        plt.plot(x[i],y[i],"y^")
+p = int(input("Enter saving%"))
+q = int(input("Enter no. of good habit"))
+k=int(input("Enter k"))
+plt.plot(p,q,'b*')
+disx=[]
+disy=[]
+dis=[]
+if (k>len(f)):
+    k=len(f)
+for i in range(len(x)):
+    dis=np.append(dis,math.sqrt(((p-x[i])**2)+((q-y[i])**2)))
+print(dis)
+dis.sort()
+min1=[]
+for i in range(k):
+    min1=np.append(min1,dis[i])
+print(min1)
+sum1=0
+for i in range(len(min1)):
+    sum1=sum1+min1[i]
+print(sum1/len(min1)) #avgmin = sum1/len(min1)
+plt.show()